Overview

Brought to you by YData

Dataset statistics

Number of variables15
Number of observations106800
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 MiB
Average record size in memory165.5 B

Variable types

Numeric14
Categorical1

Alerts

eeg_label_offset_seconds is highly overall correlated with eeg_sub_id and 2 other fieldsHigh correlation
eeg_sub_id is highly overall correlated with eeg_label_offset_seconds and 2 other fieldsHigh correlation
spectrogram_label_offset_seconds is highly overall correlated with eeg_label_offset_seconds and 2 other fieldsHigh correlation
spectrogram_sub_id is highly overall correlated with eeg_label_offset_seconds and 2 other fieldsHigh correlation
label_id has unique values Unique
eeg_sub_id has 17089 (16.0%) zeros Zeros
eeg_label_offset_seconds has 17089 (16.0%) zeros Zeros
spectrogram_sub_id has 11138 (10.4%) zeros Zeros
spectrogram_label_offset_seconds has 11138 (10.4%) zeros Zeros
seizure_vote has 73906 (69.2%) zeros Zeros
lpd_vote has 77675 (72.7%) zeros Zeros
gpd_vote has 82027 (76.8%) zeros Zeros
lrda_vote has 77294 (72.4%) zeros Zeros
grda_vote has 73101 (68.4%) zeros Zeros
other_vote has 58167 (54.5%) zeros Zeros

Reproduction

Analysis started2025-03-09 22:01:11.618616
Analysis finished2025-03-09 22:01:29.688720
Duration18.07 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

eeg_id
Real number (ℝ)

Distinct17089
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1043874 × 109
Minimum568657
Maximum4.2949584 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:29.773443image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum568657
5-th percentile2.2236912 × 108
Q11.0268956 × 109
median2.0713257 × 109
Q33.172787 × 109
95-th percentile4.0701555 × 109
Maximum4.2949584 × 109
Range4.2943897 × 109
Interquartile range (IQR)2.1458913 × 109

Descriptive statistics

Standard deviation1.2333706 × 109
Coefficient of variation (CV)0.58609486
Kurtosis-1.192152
Mean2.1043874 × 109
Median Absolute Deviation (MAD)1.0691836 × 109
Skewness0.062993347
Sum2.2474858 × 1014
Variance1.5212031 × 1018
MonotonicityNot monotonic
2025-03-09T17:01:29.875794image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2259539799 743
 
0.7%
2428433259 664
 
0.6%
1641054670 562
 
0.5%
2860052642 534
 
0.5%
525664301 531
 
0.5%
1712056492 433
 
0.4%
1480985066 416
 
0.4%
188361788 412
 
0.4%
3525185677 286
 
0.3%
1596590162 275
 
0.3%
Other values (17079) 101944
95.5%
ValueCountFrequency (%)
568657 4
 
< 0.1%
582999 11
< 0.1%
642382 2
 
< 0.1%
751790 1
 
< 0.1%
778705 1
 
< 0.1%
1629671 17
< 0.1%
1895581 1
 
< 0.1%
2061593 1
 
< 0.1%
2078097 1
 
< 0.1%
2366870 6
 
< 0.1%
ValueCountFrequency (%)
4294958358 1
 
< 0.1%
4294858825 5
 
< 0.1%
4294455489 1
 
< 0.1%
4293843368 1
 
< 0.1%
4293354003 1
 
< 0.1%
4293306306 1
 
< 0.1%
4293144208 2
 
< 0.1%
4292843598 15
< 0.1%
4292809326 3
 
< 0.1%
4291744526 8
< 0.1%

eeg_sub_id
Real number (ℝ)

High correlation  Zeros 

Distinct743
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.286189
Minimum0
Maximum742
Zeros17089
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:29.963902image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q316
95-th percentile131
Maximum742
Range742
Interquartile range (IQR)15

Descriptive statistics

Standard deviation69.757658
Coefficient of variation (CV)2.653776
Kurtosis31.809687
Mean26.286189
Median Absolute Deviation (MAD)5
Skewness5.1640972
Sum2807365
Variance4866.1308
MonotonicityNot monotonic
2025-03-09T17:01:30.075117image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17089
16.0%
1 10765
 
10.1%
2 8792
 
8.2%
3 7362
 
6.9%
4 6044
 
5.7%
5 5102
 
4.8%
6 4268
 
4.0%
7 3601
 
3.4%
8 3115
 
2.9%
9 2662
 
2.5%
Other values (733) 38000
35.6%
ValueCountFrequency (%)
0 17089
16.0%
1 10765
10.1%
2 8792
8.2%
3 7362
6.9%
4 6044
 
5.7%
5 5102
 
4.8%
6 4268
 
4.0%
7 3601
 
3.4%
8 3115
 
2.9%
9 2662
 
2.5%
ValueCountFrequency (%)
742 1
< 0.1%
741 1
< 0.1%
740 1
< 0.1%
739 1
< 0.1%
738 1
< 0.1%
737 1
< 0.1%
736 1
< 0.1%
735 1
< 0.1%
734 1
< 0.1%
733 1
< 0.1%

eeg_label_offset_seconds
Real number (ℝ)

High correlation  Zeros 

Distinct1502
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.81723
Minimum0
Maximum3372
Zeros17089
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:30.174153image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median26
Q382
95-th percentile540
Maximum3372
Range3372
Interquartile range (IQR)76

Descriptive statistics

Standard deviation314.5578
Coefficient of variation (CV)2.647409
Kurtosis35.76774
Mean118.81723
Median Absolute Deviation (MAD)26
Skewness5.4743477
Sum12689680
Variance98946.611
MonotonicityNot monotonic
2025-03-09T17:01:30.272964image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17089
 
16.0%
2 4284
 
4.0%
4 4125
 
3.9%
6 3668
 
3.4%
8 3321
 
3.1%
10 3125
 
2.9%
12 2878
 
2.7%
14 2646
 
2.5%
16 2380
 
2.2%
18 2218
 
2.1%
Other values (1492) 61066
57.2%
ValueCountFrequency (%)
0 17089
16.0%
2 4284
 
4.0%
4 4125
 
3.9%
6 3668
 
3.4%
8 3321
 
3.1%
10 3125
 
2.9%
12 2878
 
2.7%
14 2646
 
2.5%
16 2380
 
2.2%
18 2218
 
2.1%
ValueCountFrequency (%)
3372 1
< 0.1%
3366 1
< 0.1%
3364 1
< 0.1%
3362 1
< 0.1%
3352 1
< 0.1%
3350 1
< 0.1%
3346 1
< 0.1%
3344 1
< 0.1%
3342 1
< 0.1%
3340 1
< 0.1%

spectrogram_id
Real number (ℝ)

Distinct11138
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0672624 × 109
Minimum353733
Maximum2.1473884 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:30.372937image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum353733
5-th percentile91036433
Q15.2386258 × 108
median1.0579043 × 109
Q31.6231954 × 109
95-th percentile2.0329331 × 109
Maximum2.1473884 × 109
Range2.1470346 × 109
Interquartile range (IQR)1.0993329 × 109

Descriptive statistics

Standard deviation6.291475 × 108
Coefficient of variation (CV)0.58949653
Kurtosis-1.2358003
Mean1.0672624 × 109
Median Absolute Deviation (MAD)5.448347 × 108
Skewness0.018177563
Sum1.1398363 × 1014
Variance3.9582657 × 1017
MonotonicityIncreasing
2025-03-09T17:01:30.481077image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
764146759 1022
 
1.0%
1974785580 836
 
0.8%
1391458063 743
 
0.7%
1863712617 703
 
0.7%
577118473 562
 
0.5%
840003147 534
 
0.5%
365931891 531
 
0.5%
12849827 449
 
0.4%
1568768668 444
 
0.4%
1254544437 440
 
0.4%
Other values (11128) 100536
94.1%
ValueCountFrequency (%)
353733 9
< 0.1%
924234 2
 
< 0.1%
999431 11
< 0.1%
1084844 6
< 0.1%
1219001 7
< 0.1%
1353070 1
 
< 0.1%
1730458 5
< 0.1%
1872874 8
< 0.1%
1910466 5
< 0.1%
2207717 4
 
< 0.1%
ValueCountFrequency (%)
2147388374 11
< 0.1%
2147312808 5
 
< 0.1%
2146798838 4
 
< 0.1%
2146414988 1
 
< 0.1%
2146188334 3
 
< 0.1%
2146170054 13
< 0.1%
2146166212 22
< 0.1%
2145983945 10
< 0.1%
2145846010 7
 
< 0.1%
2145805074 1
 
< 0.1%

spectrogram_sub_id
Real number (ℝ)

High correlation  Zeros 

Distinct1022
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.733596
Minimum0
Maximum1021
Zeros11138
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:30.572684image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q329
95-th percentile237
Maximum1021
Range1021
Interquartile range (IQR)27

Descriptive statistics

Standard deviation104.29212
Coefficient of variation (CV)2.384714
Kurtosis23.37504
Mean43.733596
Median Absolute Deviation (MAD)7
Skewness4.3906989
Sum4670748
Variance10876.846
MonotonicityNot monotonic
2025-03-09T17:01:30.666466image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11138
 
10.4%
1 8708
 
8.2%
2 7429
 
7.0%
3 6417
 
6.0%
4 5494
 
5.1%
5 4772
 
4.5%
6 4085
 
3.8%
7 3533
 
3.3%
8 3124
 
2.9%
9 2752
 
2.6%
Other values (1012) 49348
46.2%
ValueCountFrequency (%)
0 11138
10.4%
1 8708
8.2%
2 7429
7.0%
3 6417
6.0%
4 5494
5.1%
5 4772
4.5%
6 4085
 
3.8%
7 3533
 
3.3%
8 3124
 
2.9%
9 2752
 
2.6%
ValueCountFrequency (%)
1021 1
< 0.1%
1020 1
< 0.1%
1019 1
< 0.1%
1018 1
< 0.1%
1017 1
< 0.1%
1016 1
< 0.1%
1015 1
< 0.1%
1014 1
< 0.1%
1013 1
< 0.1%
1012 1
< 0.1%

spectrogram_label_offset_seconds
Real number (ℝ)

High correlation  Zeros 

Distinct4686
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean520.4314
Minimum0
Maximum17632
Zeros11138
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:30.772064image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median62
Q3394
95-th percentile2490.1
Maximum17632
Range17632
Interquartile range (IQR)382

Descriptive statistics

Standard deviation1449.7599
Coefficient of variation (CV)2.7856887
Kurtosis47.181716
Mean520.4314
Median Absolute Deviation (MAD)62
Skewness6.0947306
Sum55582074
Variance2101803.7
MonotonicityNot monotonic
2025-03-09T17:01:31.014782image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11138
 
10.4%
2 3224
 
3.0%
4 3096
 
2.9%
6 2786
 
2.6%
8 2491
 
2.3%
10 2359
 
2.2%
12 2166
 
2.0%
14 1998
 
1.9%
16 1813
 
1.7%
18 1630
 
1.5%
Other values (4676) 74099
69.4%
ValueCountFrequency (%)
0 11138
10.4%
2 3224
 
3.0%
4 3096
 
2.9%
6 2786
 
2.6%
8 2491
 
2.3%
10 2359
 
2.2%
12 2166
 
2.0%
14 1998
 
1.9%
16 1813
 
1.7%
18 1630
 
1.5%
ValueCountFrequency (%)
17632 1
< 0.1%
17630 1
< 0.1%
17626 1
< 0.1%
17624 1
< 0.1%
17622 1
< 0.1%
17620 1
< 0.1%
17618 1
< 0.1%
17616 1
< 0.1%
17614 1
< 0.1%
17612 1
< 0.1%

label_id
Real number (ℝ)

Unique 

Distinct106800
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1414148 × 109
Minimum338
Maximum4.2949335 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:31.114426image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum338
5-th percentile2.1031044 × 108
Q11.0674194 × 109
median2.138332 × 109
Q33.2178159 × 109
95-th percentile4.0813579 × 109
Maximum4.2949335 × 109
Range4.2949332 × 109
Interquartile range (IQR)2.1503964 × 109

Descriptive statistics

Standard deviation1.2416697 × 109
Coefficient of variation (CV)0.57983615
Kurtosis-1.2000132
Mean2.1414148 × 109
Median Absolute Deviation (MAD)1.0752523 × 109
Skewness0.0081215305
Sum2.287031 × 1014
Variance1.5417437 × 1018
MonotonicityNot monotonic
2025-03-09T17:01:31.197693image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127492639 1
 
< 0.1%
2280293819 1
 
< 0.1%
211430718 1
 
< 0.1%
1209816356 1
 
< 0.1%
2728965724 1
 
< 0.1%
3832244487 1
 
< 0.1%
1342527369 1
 
< 0.1%
871762682 1
 
< 0.1%
457395995 1
 
< 0.1%
3253065483 1
 
< 0.1%
Other values (106790) 106790
> 99.9%
ValueCountFrequency (%)
338 1
< 0.1%
29652 1
< 0.1%
94683 1
< 0.1%
99525 1
< 0.1%
117889 1
< 0.1%
120688 1
< 0.1%
218991 1
< 0.1%
244789 1
< 0.1%
265836 1
< 0.1%
296654 1
< 0.1%
ValueCountFrequency (%)
4294933502 1
< 0.1%
4294920358 1
< 0.1%
4294888279 1
< 0.1%
4294766404 1
< 0.1%
4294748510 1
< 0.1%
4294736565 1
< 0.1%
4294658018 1
< 0.1%
4294489914 1
< 0.1%
4294459484 1
< 0.1%
4294457275 1
< 0.1%

patient_id
Real number (ℝ)

Distinct1950
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32304.428
Minimum56
Maximum65494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:31.305812image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile2641
Q116707
median32068
Q348036
95-th percentile61563
Maximum65494
Range65438
Interquartile range (IQR)31329

Descriptive statistics

Standard deviation18538.196
Coefficient of variation (CV)0.57385929
Kurtosis-1.1149384
Mean32304.428
Median Absolute Deviation (MAD)15527
Skewness0.0037500558
Sum3.450113 × 109
Variance3.4366472 × 108
MonotonicityNot monotonic
2025-03-09T17:01:31.404638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30631 2215
 
2.1%
2641 2185
 
2.0%
35627 1403
 
1.3%
28330 1362
 
1.3%
54199 1350
 
1.3%
35225 1288
 
1.2%
57378 1165
 
1.1%
38549 1012
 
0.9%
56450 952
 
0.9%
32481 942
 
0.9%
Other values (1940) 92926
87.0%
ValueCountFrequency (%)
56 60
0.1%
105 54
0.1%
149 9
 
< 0.1%
195 59
0.1%
198 10
 
< 0.1%
200 51
< 0.1%
260 23
 
< 0.1%
282 20
 
< 0.1%
312 4
 
< 0.1%
345 57
0.1%
ValueCountFrequency (%)
65494 20
 
< 0.1%
65480 9
 
< 0.1%
65442 30
 
< 0.1%
65430 46
 
< 0.1%
65378 401
0.4%
65377 4
 
< 0.1%
65368 14
 
< 0.1%
65356 149
 
0.1%
65264 21
 
< 0.1%
65250 139
 
0.1%

expert_consensus
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
Seizure
20933 
GRDA
18861 
Other
18808 
GPD
16702 
LRDA
16640 

Length

Max length7
Median length5
Mean length4.4686236
Min length3

Characters and Unicode

Total characters477249
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSeizure
2nd rowSeizure
3rd rowSeizure
4th rowSeizure
5th rowSeizure

Common Values

ValueCountFrequency (%)
Seizure 20933
19.6%
GRDA 18861
17.7%
Other 18808
17.6%
GPD 16702
15.6%
LRDA 16640
15.6%
LPD 14856
13.9%

Length

2025-03-09T17:01:31.521721image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-09T17:01:31.616362image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
seizure 20933
19.6%
grda 18861
17.7%
other 18808
17.6%
gpd 16702
15.6%
lrda 16640
15.6%
lpd 14856
13.9%

Most occurring characters

ValueCountFrequency (%)
D 67059
14.1%
e 60674
12.7%
r 39741
8.3%
G 35563
 
7.5%
R 35501
 
7.4%
A 35501
 
7.4%
P 31558
 
6.6%
L 31496
 
6.6%
S 20933
 
4.4%
i 20933
 
4.4%
Other values (5) 98290
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 477249
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
D 67059
14.1%
e 60674
12.7%
r 39741
8.3%
G 35563
 
7.5%
R 35501
 
7.4%
A 35501
 
7.4%
P 31558
 
6.6%
L 31496
 
6.6%
S 20933
 
4.4%
i 20933
 
4.4%
Other values (5) 98290
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 477249
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
D 67059
14.1%
e 60674
12.7%
r 39741
8.3%
G 35563
 
7.5%
R 35501
 
7.4%
A 35501
 
7.4%
P 31558
 
6.6%
L 31496
 
6.6%
S 20933
 
4.4%
i 20933
 
4.4%
Other values (5) 98290
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 477249
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
D 67059
14.1%
e 60674
12.7%
r 39741
8.3%
G 35563
 
7.5%
R 35501
 
7.4%
A 35501
 
7.4%
P 31558
 
6.6%
L 31496
 
6.6%
S 20933
 
4.4%
i 20933
 
4.4%
Other values (5) 98290
20.6%

seizure_vote
Real number (ℝ)

Zeros 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.87802434
Minimum0
Maximum19
Zeros73906
Zeros (%)69.2%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:31.706049image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum19
Range19
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5388733
Coefficient of variation (CV)1.7526545
Kurtosis8.2088947
Mean0.87802434
Median Absolute Deviation (MAD)0
Skewness2.1785843
Sum93773
Variance2.368131
MonotonicityNot monotonic
2025-03-09T17:01:31.788473image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 73906
69.2%
3 19520
 
18.3%
1 6475
 
6.1%
2 2329
 
2.2%
5 1825
 
1.7%
4 1745
 
1.6%
6 336
 
0.3%
7 313
 
0.3%
8 91
 
0.1%
9 57
 
0.1%
Other values (8) 203
 
0.2%
ValueCountFrequency (%)
0 73906
69.2%
1 6475
 
6.1%
2 2329
 
2.2%
3 19520
 
18.3%
4 1745
 
1.6%
5 1825
 
1.7%
6 336
 
0.3%
7 313
 
0.3%
8 91
 
0.1%
9 57
 
0.1%
ValueCountFrequency (%)
19 4
 
< 0.1%
16 3
 
< 0.1%
15 36
 
< 0.1%
14 25
 
< 0.1%
13 30
 
< 0.1%
12 22
 
< 0.1%
11 29
 
< 0.1%
10 54
0.1%
9 57
0.1%
8 91
0.1%

lpd_vote
Real number (ℝ)

Zeros 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1387828
Minimum0
Maximum18
Zeros77675
Zeros (%)72.7%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:31.861888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.8188453
Coefficient of variation (CV)2.4753143
Kurtosis11.05233
Mean1.1387828
Median Absolute Deviation (MAD)0
Skewness3.2892374
Sum121622
Variance7.9458886
MonotonicityNot monotonic
2025-03-09T17:01:31.951494image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 77675
72.7%
1 9680
 
9.1%
2 4618
 
4.3%
3 4011
 
3.8%
4 2290
 
2.1%
5 1323
 
1.2%
6 1065
 
1.0%
7 863
 
0.8%
13 769
 
0.7%
14 739
 
0.7%
Other values (9) 3767
 
3.5%
ValueCountFrequency (%)
0 77675
72.7%
1 9680
 
9.1%
2 4618
 
4.3%
3 4011
 
3.8%
4 2290
 
2.1%
5 1323
 
1.2%
6 1065
 
1.0%
7 863
 
0.8%
8 616
 
0.6%
9 574
 
0.5%
ValueCountFrequency (%)
18 45
 
< 0.1%
17 120
 
0.1%
16 92
 
0.1%
15 557
0.5%
14 739
0.7%
13 769
0.7%
12 589
0.6%
11 545
0.5%
10 629
0.6%
9 574
0.5%

gpd_vote
Real number (ℝ)

Zeros 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2649251
Minimum0
Maximum16
Zeros82027
Zeros (%)76.8%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:32.028740image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1318887
Coefficient of variation (CV)2.4759479
Kurtosis6.6558296
Mean1.2649251
Median Absolute Deviation (MAD)0
Skewness2.7555029
Sum135094
Variance9.8087268
MonotonicityNot monotonic
2025-03-09T17:01:32.107625image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 82027
76.8%
1 5643
 
5.3%
2 4352
 
4.1%
3 2756
 
2.6%
10 2052
 
1.9%
11 1445
 
1.4%
9 1200
 
1.1%
4 1163
 
1.1%
12 1054
 
1.0%
13 941
 
0.9%
Other values (7) 4167
 
3.9%
ValueCountFrequency (%)
0 82027
76.8%
1 5643
 
5.3%
2 4352
 
4.1%
3 2756
 
2.6%
4 1163
 
1.1%
5 909
 
0.9%
6 573
 
0.5%
7 774
 
0.7%
8 861
 
0.8%
9 1200
 
1.1%
ValueCountFrequency (%)
16 116
 
0.1%
15 510
 
0.5%
14 424
 
0.4%
13 941
0.9%
12 1054
1.0%
11 1445
1.4%
10 2052
1.9%
9 1200
1.1%
8 861
0.8%
7 774
 
0.7%

lrda_vote
Real number (ℝ)

Zeros 

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.94829588
Minimum0
Maximum15
Zeros77294
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:32.180938image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1367987
Coefficient of variation (CV)2.2533038
Kurtosis10.561945
Mean0.94829588
Median Absolute Deviation (MAD)0
Skewness3.0783767
Sum101278
Variance4.5659088
MonotonicityNot monotonic
2025-03-09T17:01:32.264303image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 77294
72.4%
1 8177
 
7.7%
3 6597
 
6.2%
2 6122
 
5.7%
5 1621
 
1.5%
6 1449
 
1.4%
4 1279
 
1.2%
7 1190
 
1.1%
9 802
 
0.8%
8 799
 
0.7%
Other values (6) 1470
 
1.4%
ValueCountFrequency (%)
0 77294
72.4%
1 8177
 
7.7%
2 6122
 
5.7%
3 6597
 
6.2%
4 1279
 
1.2%
5 1621
 
1.5%
6 1449
 
1.4%
7 1190
 
1.1%
8 799
 
0.7%
9 802
 
0.8%
ValueCountFrequency (%)
15 55
 
0.1%
14 51
 
< 0.1%
13 357
 
0.3%
12 246
 
0.2%
11 469
 
0.4%
10 292
 
0.3%
9 802
0.8%
8 799
0.7%
7 1190
1.1%
6 1449
1.4%

grda_vote
Real number (ℝ)

Zeros 

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0591854
Minimum0
Maximum15
Zeros73101
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:32.349461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2284924
Coefficient of variation (CV)2.1039682
Kurtosis10.886845
Mean1.0591854
Median Absolute Deviation (MAD)0
Skewness3.0782446
Sum113121
Variance4.9661784
MonotonicityNot monotonic
2025-03-09T17:01:32.427073image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 73101
68.4%
3 12643
 
11.8%
1 9508
 
8.9%
2 4219
 
4.0%
6 1058
 
1.0%
5 983
 
0.9%
4 927
 
0.9%
8 923
 
0.9%
7 900
 
0.8%
13 866
 
0.8%
Other values (6) 1672
 
1.6%
ValueCountFrequency (%)
0 73101
68.4%
1 9508
 
8.9%
2 4219
 
4.0%
3 12643
 
11.8%
4 927
 
0.9%
5 983
 
0.9%
6 1058
 
1.0%
7 900
 
0.8%
8 923
 
0.9%
9 573
 
0.5%
ValueCountFrequency (%)
15 25
 
< 0.1%
14 62
 
0.1%
13 866
0.8%
12 272
 
0.3%
11 269
 
0.3%
10 471
0.4%
9 573
0.5%
8 923
0.9%
7 900
0.8%
6 1058
1.0%

other_vote
Real number (ℝ)

Zeros 

Distinct26
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9662828
Minimum0
Maximum25
Zeros58167
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size834.5 KiB
2025-03-09T17:01:32.504236image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum25
Range25
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.6211803
Coefficient of variation (CV)1.8416376
Kurtosis7.8044131
Mean1.9662828
Median Absolute Deviation (MAD)0
Skewness2.7000919
Sum209999
Variance13.112947
MonotonicityNot monotonic
2025-03-09T17:01:32.603350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 58167
54.5%
1 13471
 
12.6%
2 9782
 
9.2%
3 7286
 
6.8%
4 3081
 
2.9%
5 3016
 
2.8%
6 2153
 
2.0%
7 1544
 
1.4%
9 1228
 
1.1%
8 1061
 
1.0%
Other values (16) 6011
 
5.6%
ValueCountFrequency (%)
0 58167
54.5%
1 13471
 
12.6%
2 9782
 
9.2%
3 7286
 
6.8%
4 3081
 
2.9%
5 3016
 
2.8%
6 2153
 
2.0%
7 1544
 
1.4%
8 1061
 
1.0%
9 1228
 
1.1%
ValueCountFrequency (%)
25 5
 
< 0.1%
24 18
 
< 0.1%
23 21
 
< 0.1%
22 10
 
< 0.1%
21 93
 
0.1%
20 303
0.3%
19 181
 
0.2%
18 454
0.4%
17 545
0.5%
16 326
0.3%

Interactions

2025-03-09T17:01:28.049112image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:13.700274image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.746599image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.838379image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.066327image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.120266image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.174679image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.293596image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.451860image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.518433image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.596521image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.807888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.902571image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.981261image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.117273image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:13.777307image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.819082image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.913366image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.140142image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.188840image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.247840image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.363269image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.524484image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.591779image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.669098image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.883880image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.976878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.051523image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.331191image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:13.850497image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.895765image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.993654image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.221644image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.259416image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.329239image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.433897image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.603789image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.666835image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.747838image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.958698image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.055707image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.128201image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.406070image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:13.928600image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.979437image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.074357image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.293152image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.344078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.410676image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.516888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.681383image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.747988image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.827651image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.040162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.149868image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.208861image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.474525image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:13.999300image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.052894image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.144352image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.368082image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.409503image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.486247image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.585651image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.750745image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.823789image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.901524image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.112639image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.224051image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.283363image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.546721image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.067364image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.129306image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.223447image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.440004image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.484933image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.562539image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.791092image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.826543image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.898286image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.974731image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.190417image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.294878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.361079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.624599image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.149203image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.209373image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.300328image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.516042image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.564315image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.645268image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.869084image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.906647image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.979289image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.049707image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.266411image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.373378image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.442852image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.692713image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.220798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.277056image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.380860image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.585075image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.636354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.720554image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.936328image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.977142image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.049777image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.123993image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.344286image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.448369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.519383image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.765632image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.300450image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.361046image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.460365image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.662712image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.709711image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.801183image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.008759image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.049052image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.126067image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.200024image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.428668image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.526648image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.594510image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.839210image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.375403image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.441207image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.541533image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.741257image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.789683image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.885559image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.084672image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.131594image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.203097image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.276744image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.508055image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.597773image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.663856image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.914288image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.453676image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.519560image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.616754image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.820074image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.867779image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.975272image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.159931image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.208892image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.281998image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.491980image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.589756image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.682441image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.749182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:28.988208image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.529465image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.603034image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.706933image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.896274image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.949356image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.057479image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.235027image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.286600image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.364709image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.578448image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.671186image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.759438image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.829630image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:29.056917image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.605456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.678766image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.785112image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:17.972212image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.024350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.134476image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.309957image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.366838image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.444948image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.658624image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.748393image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.834917image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.906100image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:29.132312image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:14.678527image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:15.762905image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:16.986771image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:18.047250image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:19.103440image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:20.219270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:21.386073image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:22.442635image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:23.523961image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:24.738723image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:25.828333image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:26.907979image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-03-09T17:01:27.981175image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2025-03-09T17:01:32.671548image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
eeg_ideeg_label_offset_secondseeg_sub_idexpert_consensusgpd_votegrda_votelabel_idlpd_votelrda_voteother_votepatient_idseizure_votespectrogram_idspectrogram_label_offset_secondsspectrogram_sub_id
eeg_id1.000-0.034-0.0310.0600.0080.0330.003-0.006-0.0060.0260.0170.014-0.007-0.023-0.025
eeg_label_offset_seconds-0.0341.0000.9420.1230.0910.087-0.001-0.0260.068-0.196-0.0240.096-0.0130.5900.790
eeg_sub_id-0.0310.9421.0000.1290.1290.126-0.001-0.0430.163-0.207-0.0240.028-0.0150.5350.820
expert_consensus0.0600.1230.1291.0000.3910.3870.0060.3520.3870.3140.1430.4120.0740.1040.119
gpd_vote0.0080.0910.1290.3911.000-0.031-0.0040.058-0.1960.074-0.0070.024-0.0300.1160.137
grda_vote0.0330.0870.1260.387-0.0311.000-0.000-0.1780.0050.1320.001-0.3470.019-0.0380.049
label_id0.003-0.001-0.0010.006-0.004-0.0001.000-0.004-0.003-0.004-0.0050.003-0.001-0.001-0.003
lpd_vote-0.006-0.026-0.0430.3520.058-0.178-0.0041.0000.1210.1260.011-0.1770.0050.1230.063
lrda_vote-0.0060.0680.1630.387-0.1960.005-0.0030.1211.0000.2190.042-0.257-0.0130.0380.155
other_vote0.026-0.196-0.2070.3140.0740.132-0.0040.1260.2191.0000.041-0.3060.021-0.082-0.167
patient_id0.017-0.024-0.0240.143-0.0070.001-0.0050.0110.0420.0411.000-0.0640.029-0.023-0.028
seizure_vote0.0140.0960.0280.4120.024-0.3470.003-0.177-0.257-0.306-0.0641.000-0.018-0.006-0.021
spectrogram_id-0.007-0.013-0.0150.074-0.0300.019-0.0010.005-0.0130.0210.029-0.0181.0000.0170.002
spectrogram_label_offset_seconds-0.0230.5900.5350.1040.116-0.038-0.0010.1230.038-0.082-0.023-0.0060.0171.0000.854
spectrogram_sub_id-0.0250.7900.8200.1190.1370.049-0.0030.0630.155-0.167-0.028-0.0210.0020.8541.000

Missing values

2025-03-09T17:01:29.230548image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-09T17:01:29.440456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

eeg_ideeg_sub_ideeg_label_offset_secondsspectrogram_idspectrogram_sub_idspectrogram_label_offset_secondslabel_idpatient_idexpert_consensusseizure_votelpd_votegpd_votelrda_votegrda_voteother_vote
0162818074200.035373300.012749263942516Seizure300000
1162818074216.035373316.0388756311342516Seizure300000
2162818074228.035373328.0114267048842516Seizure300000
31628180742318.0353733318.0271899117342516Seizure300000
41628180742424.0353733424.0308063200942516Seizure300000
51628180742526.0353733526.0241309160542516Seizure300000
61628180742630.0353733630.036459393042516Seizure300000
71628180742736.0353733736.0381148357342516Seizure300000
81628180742840.0353733840.0338871849442516Seizure300000
9227739260300.092423400.0197880740430539GPD005015
eeg_ideeg_sub_ideeg_label_offset_secondsspectrogram_idspectrogram_sub_idspectrogram_label_offset_secondslabel_idpatient_idexpert_consensusseizure_votelpd_votegpd_votelrda_votegrda_voteother_vote
10679035191726912.0214738837412.0191629961610351LRDA000300
10679135191726924.0214738837424.0108598802910351LRDA000300
10679235191726936.0214738837436.0380897544710351LRDA000300
10679335191726948.0214738837448.0137411563310351LRDA000300
106794351917269510.02147388374510.022373984510351LRDA000300
106795351917269612.02147388374612.0419567730710351LRDA000300
106796351917269714.02147388374714.029089667510351LRDA000300
106797351917269816.02147388374816.046143545110351LRDA000300
106798351917269918.02147388374918.0378621313110351LRDA000300
1067993519172691020.021473883741020.0364271617610351LRDA000300